seongju/kor-3i4k-bert-base-cased
09
Model information
- language : Korean
- fine tuning data : kor_3i4k
- License : CC-BY-SA 4.0
- Base model : bert-base-multilingual-cased
- input : sentence
- output : intent
Train information
- train_runtime: 2376.638
- trainstepsper_second: 2.175
- train_loss: 0.356829648599977
- epoch: 3.0
How to use
from transformers import AutoTokenizer, AutoModelForSequenceClassification
tokenizer = AutoTokenizer.from_pretrained (
"seongju/kor-3i4k-bert-base-cased"
)
model = AutoModelForSequenceClassification.from_pretrained (
"seongju/kor-3i4k-bert-base-cased"
)
inputs = tokenizer(
"너는 지금 무엇을 하고 있니?",
padding=True, truncation=True, max_length=128, return_tensors="pt"
)
outputs = model(**inputs)
probs = outputs[0].softmax(1)
output = probs.argmax().item()